2014/3/11

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5G: A Paradigm Shift of Cellular Networks

Electronic Engineering, Tsinghua UniversityTsinghua National Lab for Information Science and Technology

March 7, 2014

Zhisheng Niu

Tokyo Wireless Technology Summit 2014

Migration of Mobile Communications

• Cooper’s Law: “The data rate available to a wireless device doubles roughly every 30 months” (Martin Cooper)– This has held for over 50 yrs, leading to 1,000,000x increase – Technology: 1G (’80s) 2G (’90s) 3G (’00s) 4G (’10s)

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“People always over-estimate things for 3 years scope,

but under-estimate things for 10 year scope”

– Bill Gates

What does 5G look like?

What will the enabling technologies be for 5G?

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What’s the technology that mostly contributed to this success?

TDMA? CDMA? AMC? Turbo? OFDM? MIMO? ……

To answer this question, we need understand

25x 5x 5x

1600x

0

500

1000

1500

2000

widerspectrum

dividing thespectrum intosmaller slices

bettermodulationscheme

reduced cellsizes

Wireless Capacity…

Source: William Webb, Ofcom

It’s Cellular!

Cellular was invented for spectrum-efficiency

But, is it really energy‐efficient? Is it smart enough to support massive M2M connections?  

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This has not been a major concern

Energy of firewood:16.2 megajoules/kgOnly one bit: invasion or no-invasion

Extremely energy inefficient, yet needed5

But, it is a big concern today

• But, energy consumption and cost increased dramatically – Globally, #BS > 5 million, #Users>5 billion, EC> 100bn KWh (2012)

– As 4G/5G deploys and IoT boosts, EC & Connections grow dramatically

– Energy cost is also increasing (price and environmental impact)

How to carry 1000X traffic and connections using limited spectrum & energy?

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EE as a key decision-making factor

Equipment Type TEEER Formula Min. TEEER Allowable

Transport ‐log (Ptotal / Throughput) 7.54

optical and Video 7.54

P2P Microwave 5.75

Switch/Router ‐log (Ptotal / Forwarding Capacity) 7.67

Media Gateway ‐log (Ptotal / Throughput) 6.54

Access (Access Lines / Ptotal ) +1 2.50

Power (POut Total / PIn Total ) X 10 9.20

Power Amplifier (Wireless)

(Total RF Output Power / Total Input Power) X 10

1.05

Base Station ? ?

Verizon’s TEEER (Telecom Equipment Energy Efficiency Rating) since 2009 

www.verizonnebs.com/TPRs/VZ-TPR-9207.pdf

Ptotal = 0.35 x Pmax + 0.40 x P50% load + 0.25 x Psleep

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Smartness was also not an issue, but

Densely and randomly deployed

2G/3G/4G Coexisting (HetNet)  

J. Andrews, “Seven Ways that HetNets are Cellular Paradigm Shift”, IEEE ComMag, March 2013 8

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Diversified Needs for 5G

• Mobile traffic will have another exp. growth by 2020– Capacity-hungry video dominates: higher SE and EE (Green)– Control-intensive massive connections access should be Smarter

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5G Cellular: Greener and Smarter

Capacity-oriented

2000

Coverage‐oriented

Traffic Vo

lum

e or E

nerg

y Co

nsu

mp

tion Time

2G

Energy-oriented

2010

3G3G+

4G4G

Traffic Volume

Green&

Smart

2020

Energy Consumption

5G

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LTE‐A

LTE

GREEN

PHY approach only is no more enough

Energy-Spectrum Tradeoff in Wireless Transmissions

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– 1G (’80s): Analog, Voice, FDMA, Macro (Coverage-oriented)

– 2G (’90s): Digital, Voice, TDMA, Macro (Coverage-oriented)

– 3G (’00s): Digital, Data, CDMA, Micro (SE-oriented)

– 4G (’10s): Digital, Video, OFDMA, Pico/Femto (SE-oriented)

– 5G (’20s): Digital, Video/M2M, BDMA?, ????? (SE/EE-oriented)

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5G: A Paradigm Shift of Cellular Architecture

Cell densification is trying to further improve SE, but is it

also good for EE and smart enough to support M2M?

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Energy Waste in Existing Cellular

Traffic data from 319 HSPA cells in a European capital city measured from Jan. 1-22 2009 (Ericsson)

3 sector HSPA Site

1 25 50 75 1000

10

20

30

40

50

60

70

80

90

100

Load [%]

DC

Pow

er C

onsu

mpt

ion

[%]

OtherFans

RU3

RU2

RU1Base band

80% of the BSs are quite lightly loaded for 80% of the time, but still consume (waste) a lot of energy

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Why so many BSs under‐utilized, while still need to be densely deployed in some area?  

Existing cellular is neither smart nor green

Why lightly‐loaded BSs can’t be switched off (sleep)? 

- Mobile traffic is highly dynamic!

- BSs need to provide data services as well as network coverage simultaneously

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Ways to Reduce Energy Waste

• Exploiting traffic dynamics (reduce energy consumption when traffic is low)

– Targeting THROUGHPUT rather than CAPACITY per joule

• Exploit energy model (much energy is consumed at BB/PA/AC rather than RF, therefore BS sleeping is the most efficient way for energy saving)

– Targeting TOTAL ENERGY rather than RF power reduction only

• Exploit cell collaboration (cell densification and HetNet make cell collaboration possible, helping to turn more BSs off)

– Targeting NETWORK rather than LINK/CELL performance

• GREEN: Globally Resource-optimized & Energy-Efficient Networks

– GREEN should be a holistic approach with paradigm shift

– 5G Cellular networks should be more smart and GREEN

Key idea: Reduce Energy Waste by Adapting to Real-traffic Dynamics (REWARD)

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Tango: Traffic-aware network planning & green operation- Adapted to traffic distribution (temporally and spatially non-uniform) - Adapted to traffic characteristics (unicast, multicast, broadcast)- Adapted to QoS requirements (realtime, nonrealtime)

5G Cellular: Adapt to Traffic Dynamics(Traffic dynamics can provide opportunities for energy saving)

0:00 12:00 24:00

Power

t

Reduced Consumption

Usual Power Consumption (non-adaptive)

Traffic

Key challenge: How to guarantee the coverage and QoS?How to model and predict traffic dynamics?

Z. Niu, “TANGO: Traffic-Aware Network Planning and Green Operation”,IEEE Wireless Commun., Oct.2011 (invited article)

BS Sleep

Power Adaptation

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Example: Cell Zooming

Z. Niu, Y. Wu, J. Gong, Z. Yang, “Cell zooming for cost-efficient green cellular network,” IEEE ComMag, Nov. 2010 (IEEE APB Best Paper Award 2014)

• Cell Zooming for Smart Cellular Network

Central cell zooms in as traffic load increases

Central cell zooms out as traffic load decreases

Central cell sleeps as traffic load getting quite low

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A Dynamic Programing Approach for BS Sleeping

x-axis (m)

y-a

xis

(m

)

500 1000 1500 2000 2500 3000

500

1000

1500

2000

2500

High Load

Medium

Low Load

Active cells

Sleeping cells

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J. Gong, S. Zhou, Z. Niu, “A Dynamic Programming Approach for Base Station Sleeping in Cellular Networks,” IEICE Trans. Commun., Vol.E95-B, No.2, pp.551-562, Feb. 2012

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5G Cellular: Adapt to Environment(BS collaboration can provide opportunities for energy saving)

• CHORUS: Collaborative & Harmonized Open Radio Ubiquitous System– Open Radio: spectrum in HetNet are shared by multi-modal terminals (software defined radio)

– Globally optimized: cross-layer cross-node cross-network/system (software defined network)

cross-netw

ork/systemdesign

cross-layer cross-node design

[1] S. Zhou, Z. Niu, S. Tanabe, “CHORUS: Collaborative and Harmonized Open Radio Ubiquitous Systems”, 4th Intl. Conf. Commun. Sys. & Nets. (COMSNETS), Bangalore, India, Jan. 2012 (invited)[2] S. Zhou, Z. Niu, S. Tanabe, and P. Yang, “CHORUS: Framework for Scalable Collaboration in Heterogeneous Networks with Cognitive Synergy,” IEEE Wireless Commun. Mag, accepted, 2012

Challenges: 1) How to detect the NSI? (information explosion and incompleteness?)2) How to virtualize the network resources? (self-optimizing networks)

HetNet

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Example: BS Sharing

B. Leng, P. Mansourifard, B. Krishnamachari, “Microeconomic Analysis of Base-Station Sharing in Green Cellular Networks”, IEEE INFOCOM 2014, Toronto, Canada, April 2014

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5G Cellular: Deal with the Dilemma

Capacity‐hungry Apps (e.g., mobile videos)

Higher SE

Higher EE

Control‐intensive Apps (e.g., M2M, social networking)

Faster Connectivity

Higher Reliability

?Smaller cells Larger cells

C-plane larger

D-plane smaller

decouple

Less signaling overhead

Global optimization

SmartCoverage-on-demand

Densely deployed

Green21

Hyper Cellular for Green and Smart

• Decouple control and data coverage so that data cells could be more adaptive to traffic dynamics and network state, and control cells can take global optimization

Traffic analysis

Broad

ban

dNarro

wban

d

Signalin

g

Contro

l

GSM

3G

Macro

Micro

Hyper

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Hyper-cellular: Virtual (Elastic) Coverage

Decouple of signaling coverage and traffic coverage

Signaling coverage is seamless and traffic coverage is reconfigurable

Challenge: unified signaling for virtualized cellular NWs

U‐Plane

C‐Plane

Seamless

Elastic

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Technical Challenges

• How to decouple signaling from data coverage? How to integrate the signaling functions of HetNets? – Complete decoupling may lead to new bottleneck and delays due to frequent

visits to signaling-BSs (main difference from BCG2), but which functions should be left into the data-BSs?

• How to guarantee signaling coverage highly reliable? – Need new protocol for S-BSs. Also, tradeoff between reliability and delay

• How to detect user behaviors, QoS requests, terminal capability, and provide services in an EE manner? – Data mining, cognitive radio, on-line learning, …

• How to locate users and associate them to the best D-BS? – The best cells may be in sleeping state, activate or not?

• How to balance the EC of network parts and user terminals? – User terminals need to keep associations with S-BS in a wider scope

• ……Z. Niu, S. Zhou, S. Zhou, X. Zhong, J. Wang, “A Hyper-Cellular Paradigm for Globally Resource-optimized and Energy-Efficient Networks (GREEN)”, Science in China, Sep. 2012 (in Chinese） 24

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Global Research Activities on “5G”

• “BDMA and Relay with group cooperation” (Korea, 2008)

• “5G Communications Research Lab” (Univ. of Dresden, 2012.5)

– Jointly funded by National Instruments

• “₤35m for 5G Research Centre” (Univ. of Surrey, 2012.10)

– jointly funded by UK Research Partnership Investment Fund (UKRPIF) and a consortium of Huawei, Samsung, Telefonica Europe, Fujitsu Laboratories Europe, Rohde & Schwarz, and Aircom International

• “China launched a WG on 5G” (China Academy of Telecom Research, 2012.11)

• “Huawei invests $600m for 10Gbps 5G network” (2013.11)

• “Korea to spend $1.5 billion on 5G mobile network” (2014.1)

• “China Mobile joined NGMN 5G Alliance” (MWC2014, 2014.2)

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Global Research Activities on “5G”

• “€50m EU research grants to develop '5G' technology” (EC, 2013.2)– METIS: Mobile and wireless communications Enablers for Twenty-twenty (2020)

Information Society (SWE Ericsson, 29 partners) specifies 5G should provide 1000X higher mobile data volume per area

10‐100X higher No. connected devices for Internet of Things 10‐100X higher typical user data rate

10X longer battery life for low power M2M Communications 5X reduced e2e latency

– 5GNOW: 5th Generation Non-Orthogonal Waveforms for Asynchronous Signalling (GER)

– iJOIN: Interworking and JOINt Design of an Open Access and Backhaul Network Architecture for Small Cells based on Cloud Networks (ESP)

– TROPIC: Distributed computing, storage and radio resource allocation over cooperative femtocells (ESP)

– COMBO: joint optimisation of fixed and mobile access (GER)

– MOTO: Mobile OpportunisTic Traffic Offloading (FRA)

– PHYLAWS: PHYsical LAyer Wireless Security

• "5GrEEn - Towards Green 5G Mobile Networks“ (EIT ICT Labs. 2013.9) 26

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Green Activities in China

End-to-End Energy Efficient Networks (National 863 Program, 2012~2015)

Green Radio Excellent in Arch. and Tech. (Huawei Program, 2010 ~ )

Globally Resource-optimized and Energy-Efficient Networks (National 973 Program, 2012~2016)

2014.3.7 Zhisheng Niu @ Tsinghua University 27

Some Research Progress in 2012/13

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How much energy can be saved by Separation?

Traditional Cell Hyper Cell

in outP k P b

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How much energy can be saved by separation?

Total power consumption of a cell: more than 50% saving

Average power consumption of a cell: robust to cell size

Z. Wang, W. Zhang, “The Capability of A Separation Architecture for Achieving Energy-efficient Cellular Networking“, IEEE TWC, 2013 (accepted)

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• Separation is not easy!– Challenge 1: difficult to categorize (millions of signal types)

– Challenge 2: Difficult to separate (complicated signal interactions)

– Challenge 3: difficult to manage (synchronization)

Standard Signal TypesCategorize & SeparateCategorize & Separate

Signal Types

Standard

State

FunctionalityFunctionality Separation?

How to Separate? - Principle

2014.3.7 Zhisheng Niu @ Tsinghua University 31

X. Xu, G. He, S. Zhang, Y. Chen and S. Xu, “On Functionality Separation for Future Green Mobile Network: Concept Study over LTE”, IEEE ComMag, May 2013

How to Separate? – State Definition

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How to Separate? - State–Functionality Mapping

State UE Activities

Network Functionalities

Syn.Broadcast of

System Information

Paging Multicast Unicast

Detached Cell Selection √ √

Idle

Acquisition and Update of System Configuration

√ √

Monitoring of Upcoming Transmission Notification

√

Cell Reselection √ √Receiving of MBMS √

Active

Acquisition and Update of System Configuration.

√ √

Monitoring of Upcoming Transmission Notification

√

Cell Handover √ √ √Receiving of MBMS √

Transmission of UE-Specific Data

√

How to Separate? - Functionality–Signal Mapping

Network

Functionality

Signal Types

Syn. PilotFrame

Control

System

Info.

Bearer

Paging

Info.

Bearer

Multicast

Info.

Bearer

Unicast

Info.

Bearer

Syn. √ △

Broadcast

of System

Information

√ △ √

Paging √ √ √

Multicast √ √ √

Unicast √ √ √

△ means this relationship may change among different standards. For example, in GSM/UMTS system, the location of system information bearer is pre-defined and the frame control signal is omitted. However, in LTE systems, the location of system information bearer will be dynamic and the frame control signal is mandatory.

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How to Separate? - Mapping to 3GPP Standard

Signal Types3GPP Standard

GSM UMTS LTE

SynchronizationFCCHSCH

SCH PSS/SSS

Pilot TSCCPICHDPCCH

S-CCPCHRS

Frame ControlAGCHSACCH

PICHMICHAICH

DPCCHS-CCPCH

PHICHPCFICHPDCCHPMCH

Paging Inform. Bearer

PCH S-CCPCH PDSCH

System Inform. Bearer

BCCHSACCH

P-CCPCHPBCH

PDSCH

Multicast Inform. Bearer

CBCH S-CCPCH PMCH

Unicast Inform. Bearer

SDCCHSACCHFACCH

TCH

S-CCPCHDPDCH

PDSCH

A Lab Demo using USRP and OpenBTS

T. Zhao, P. Yang, H. Pan, R. Deng, S. Zhou, and Z. Niu, “Software Defined Radio Implementation of Signaling Splitting in Hyper-Cellular Network,” ACM SIGCOMM Workshop of Software Radio Implementation Forum (SRIF 2013), Hong Kong, Aug. 2013.

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How densely should D-BSs be deployed?

• Problem: For given QoS, how densely should the DBs be deployed for a given coverage and QoS guarantee? – BS density should adapt to traffic dynamics (e.g., cell zooming, BS sleeping)– Deploying more smaller BSs may save energy ?!(increasing sleeping

opportunity)

[1] Z. Niu, Y. Wu, J. Gong, Z. Yang, “Cell zooming for Green cellular networks”, IEEE Com Mag, Nov. 2010 [2] X. Weng, D. Cao, Z. Niu, “Energy-Efficient Cellular Network Planning under Insufficient Cell Zooming”, IEEE VTC2011-spring, Budapest, Hungary, May 2011

0 1 2 3 4 5 60

1

2

3

4

5

6

0.5

1

1.5

2

2.5

3

3.5

4x 10

-4

0 10 20 30 400

0.05

0.1

0.15

0.2

0.25

到率

Temporal Dynamics Spatial Dynamics Insufficient Zooming Sufficient Zooming

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Optimal BS Density and Tx Power(Homogeneous Case)

Table: Optimal BS density with transmit power adaption (EARTH model)

Conclusion: Joint BS density adjustment and transmit power adaption can help to save more energy!

1. D. Cao, S. Zhou, Z. Niu, “Optimal Combination of Base Station Densities for Cost-Efficient Two-tier Heterogeneous Cellular Networks”, IEEE TWC, Sep. 2013

2. D. Cao, S. Zhou, Z. Niu, “Improving the Energy Efficiency of Two-Tier Heterogeneous Cellular Networks through Partial Spectrum Reuse”, IEEE TWC, Aug. 2013

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Optimal BS Density and Tx Power(Heterogeneous Case)

1. Two‐tier PPP models with BS density ρM and ρm

2. Always connect to the BS with highest SNR (not necessarily the nearest)

Weighted Poisson‐Voronoi Tessellation:  

f(A) follows Gamma distribution with density 

where：Stochastic Geometry Modeling

0 10 20 30 40 50 60 70 80 90 1000

10

20

30

40

50

60

70

80

90

100

X coordinate

Y c

oord

inat

e

where {CM , Cm} are deployment (energy) cost

Coverageguarantee

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Optimal BS Density and Tx Power(Heterogeneous Case)

• Dynamic BS Sleeping in Dense Urban Scenario (EARTH Model)

– CM = 780 + 28.2PM , Cm = 112 + 5.2Pm

– PM = 20W, Pm =2.42W = 0.0927 < c-1=0.3162

– Reference model: macro-only homogeneous network with no BS sleeping: total energy consumption=3.26 KW/Km2

0.82 (average)(75% saving)

Conclusion: Joint optimization of Macro/Micro‐BS densities can help to save more energy!

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Optimal BS Density – Optimal Policy(Heterogeneous Case)

;

If <c=0.3162, preferentially add  micro BSs or sleep macro BSsIf >c=0.3162, preferentially add  macro BSs or sleep micro BSs

Ratio of Micro‐BS density and Macro‐BS density ()

Total Energy Density

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Heterogeneous Networks with PSR

• PSR (Partial Spectrum Reuse) to reduce over-provisioningand potential interference (to macro BSs and among micro BSs)

Total Spectrum

Macro BS

Micro BS1

Micro BS2

Micro BS3

D. Cao, S. Zhou, Z. Niu, “Improving the Energy Efficiency of Two-Tier HetwrogeneousCellular Networks through Partial Spectrum Reuse”, to appear at IEEE TWC, Aug. 2013

Optimal β=Wm/WM?

If β<1, allocate FULL spectrum to macro BSs and PARTIAL spectrum to micro BSs; If β>1, vice versa.

2

; ( )m M

M m

C Pe c

C P

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Energy Saving Gain by PSR

PSR achieves the near-optimal performance

PSR can save up to 50% of energy consumption

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How long should a BS sleep?

• Energy-Delay Tradeoff (EDT) in BS Sleeping Control– Longer sleep can save energy, but bring delays to customers

• Wake-up Policies– N-Policy: wake up whenever N new requests come during sleep

– SV-Policy: wake up after a random sleep and then keep awake

– MV-Policy: wake up after a random sleep and sleep again if find no requests

• Challenge #1: Both energy and delay concepts need to be extended– Energy = transmitting power + circuit (processing) power + basic power

– Delay = transmitting delay + queueing delay + sleeping period

• Challenge #2: EDT should be evaluated in the whole network wide– EDT on link-level single-cell level multi-cell level

1. Z. Niu, Jianan Zhang, Xueying Guo, Sheng Zhou, “On the Energy-Delay Tradeoff in Base State Sleep Mode Operation”, IEEE ICCS2012, Singapore, 21-23 Nov., 2012 (invited)

2. X. Guo, S. Zhou, P. R. Kumar, Z. Niu, “Optimal Wake-up Mechanism for Single Base Station with Sleep Mode”, 25th International Teletraffic Congress (ITC25), Shanghai, China, Sep. 2013. (Best Paper Award)

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How long should a BS sleep?

‐ Small delay can help to save energy if well designed‐ N* is related to the switching cost in a square root form‐ Sleeping Control should be used with power adaptation 

J. Wu, Z. Niu, S. Zhou, "Traffic-Aware Base Station Sleeping Control and Power Matching for Energy-Delay Tradeoffs in Green Cellular Networks“, IEEE TWC, Vol.12, no.8, Aug. 2013

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Summary

• What’s 5G?– 5G should be a paradigm shift of cellular architecture for Green and Smart

• Major approaches towards 5G – Reduce Energy Waste by Adapting to Real-traffic Dynamics (REWARD)– Traffic-Aware Network Planning and Green Operation (TANGO)– Collaborative and Harmonized Open Radio Ubiquitous Systems (CHORUS)

• A novel Hyper Cellular architecture for 5G– Decoupling signaling functions from data services to make cellular more

adaptive and intelligent– Always-on hyper cells for coverage guarantee and on-demand data cells

• Enabling technologies for 5G– Separation of control and data coverage – Resource/network virtualization and network dimensioning– Traffic adaptation technologies, including cell zooming, BS sleeping,

coverage extension, ……– Energy-delay tradeoff can help to shift the peak and therefore save energy 46

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Concluding Remark

• from World-Wide-Web to World-Wide-Wireless

• for World-Wide-Watch & World-Wide-Wisdom

but definitely should not World-Wide-Wait

and World-Wide-Waste!

: Smart IT for Low-carbon Environment

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For more information, visit http://network.ee.tsinghua.edu.cn/niulab/?category_name=publications